<html><head><title>Data Scientist - Remote</title></head>
<body><h2>Data Scientist - Remote</h2>
As a Data Scientist in Product & Technology, you will help Paylocity discover the information hidden in vast amounts of data, to help our customers make smarter human capital decisions that drive organizational success. Your primary focus will be to apply knowledge of statistics, machine learning, programming, data modeling, simulation, and advanced mathematics to recognize patterns, identify opportunities, pose business questions, and make valuable discoveries leading to prototype development and product improvement.

Are you the teammate we are looking for?

Who you are:
Enthusiastic about advanced analytics and how predictive insights lead to a superior customer experience
Invested in staying current in data science by applying new technologies and practices
Able to work in a collaborative environment with a desire to share your ideas
Able to work independently on modules and complete tasks with high quality, but unafraid to seek out suggestions from other team members
Excited to work on cutting-edge technology!

How we work:
Curiosity and candor; the quality of the idea wins the day
Casual, focused, and agile environment operating under our shared principles
Customers at the center of everything we do
Small, mission-focused squads with an entrepreneurial spirit backed by enterprise investments
Consistent routines across stakeholders to ensure complete transparency
Close working relationship between executive stakeholders and customers

What we offer:
A compelling mission to elevate payroll and human resources across the backroom and into the boardroom
Focus on helping our customers automate manual processes, appeal to the modern workforce, and glean insights from analytics
Lean enabling process that focuses on putting our customers at the center of everything we do
A commitment to investing in our products, hiring the best talent, and giving them the chance to meaningfully contribute to a vast market opportunity
Ample opportunity and encouragement to stay current with external training
A phenomenal talent anywhere culture, where employees can work remotely anywhere in the U.S. and/or work from one of three U.S. offices located in Illinois, Florida and Idaho

What you bring:
Demonstrated ability to leverage data science to drive business results. Some ways previous successful candidates have demonstrated this are:
3-6 years of data science success at other software companies
Recognized success for data science skills via academic awards, scholarships or corporate recognition programs (Employee of the Year, etc.)
Experience in writing production grade machine learning models in Python. Some ways previous successful candidates have demonstrated this are:
A portfolio of publicly available data science projects that resulted in a fully functioning piece of software
Strong academic publication or speaking record in organizations such as ICML, NeurIPS, JML, KDD, and INFORMS
History of strong performance in Kaggle competitions
Experience with cloud infrastructure on AWS or Azure
Skilled at translating business problems into data science problems and communicating the results to non-technical audiences.
Some ways previous successful candidates have demonstrated this are:

A resume or cover letter outlining previous experience leveraging data science across many domains
A professional or academic track record of teaching mathematical or data science concepts to non-traditional audiences
Experience or interest for leveraging technology and data to empower employees. Some ways previous successful candidates have demonstrated this are:
Professional or academic experience in HR, social science or psychology
Advanced degree (Masters or PhD) preferred in computer science, industrial engineering, statistics, industrial organizational psychology, neurology, public policy, linguistics or other quantitative field preferred. Bachelor’s degree required.

During the last three months, you would have:
Selected features, built and optimized classifiers using machine learning techniques such as random forests, xgboost, TensorFlow, linear regression, time series methods
Collaborated with Product Owners, Sales Leaders, Enterprise Architects and other executives to translate complex human capital management challenges into data science projects
Extended company’s data with third party sources of information when needed
Enhanced data collection procedures to include information that is relevant for building analytic systems
Leverage cutting edge big data technologies on AWS and Microsoft Azure
Conducted ad-hoc analysis and presented results in a clear manner
Created automated anomaly detection systems and tracking of its performance
Worked closely with full stack .net engineers in an agile product development environment</body>
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